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RStudio provides a place to do your work! Other tools, communication, community, it makes your life as a chef easier. You have food to prepare, and the knife is one of the tools that you’ll use to accomplish your task.Īnd if R were a knife, RStudio is the kitchen. So what is the difference between R and RStudio? Here is an analogy to start us off. R is a great language to learn for data-oriented programming because it is widely adopted, user-friendly, and (most importantly) open source! In this course, we will use the programming language R, and the accompanying integrated development environment (IDE) RStudio. Incorporating programming into analysis workflows not only makes science more efficient, but also more computationally reproducible.

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The changing landscape of programming is making learning how to code easier than it ever has been. There is a vibrant community out there that is collectively developing increasingly easy to use and powerful open source programming tools. 22 Additional Resources: Collaboration, authorship and data policies.21 Additional Resources: Using NetCDF files.19.6 Incorporate base maps into static maps using ggmap.18 Hands On: Clean and Integrate Datasets.

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17.9 Full source code for the final application.17.6.3 Finishing touches: data citation.17.6 Extending the user interface with dynamic plots.17.4.4 Connect the slider values to the plot.17.4.3 Add sliders to set the min depth and max depth for the X axis.17.4.2 Add a simple scatterplot using ggplot.16.7 Tools in Support of Creating a DMP.15.5 Interactive visualization using leaflet and DT.15.4.2 Smarter tick labels using scales.

15.2.1 ggplot vs base vs lattice vs XYZ….14.9 Sharing and releasing your package.14.8 Checking and installing your package.12.8 Changing shape: pivot_longer() and pivot_wider().12.5 Selecting/removing columns: select().11.12 Simple Guidelines for Effective Data.11.2 Benefits of relational data systems.10.2.1 Exercise: Create and merge pull requests.8.2.1 Activity: Collaborating with a trusted colleague.8 Git: Collaboration and Conflict Management.

7.9 Collaboration and conflict free workflows.

7.7 Working locally with Git via RStudio.

7.6 Create a remote repository on GitHub.

7.3 Version control and Collaboration using Git and GitHub.

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6.7.1 Download the data to be used for the tutorial.

6.3 Data repositories: built for data (and code).

5.7.2 I just entered a command and nothing is happening.

5.5.4 Use a function to read a file into R.

5.3.2 Logical operators and expressions.

4.5.2 Updating a previous R installation.

4.2.1 What is needed for computational reproducibility?.

4 RStudio and Git/GitHub Setup and Motivation.

2.2 About the Whole Brain Thinking System.

1 Reproducible Research Techniques for Synthesis.